import java.util.Random;

import core.*;
import core.genetic.*;
import core.neural.*;
import core.sim.FunctionOptimization;


public class Test {

	
	public static void main(String[] args) {
		Random rand = new Random(2);
		double[] niz = new double[12];
		System.out.println(Math.exp(-100));
		System.out.println(Math.log(Math.exp(-100)));
//		for(int j = 0;j<8;j++) {
//		for(int i = 0;i<12;i++)
//			System.out.printf("%.3f, ",1-2*rand.nextDouble());
//		System.out.println();
//		}
		
//		double min = Double.POSITIVE_INFINITY;
//		
//		double step = 0.05;
//		for(double x = -1;x<=1.000001;x+=step)
//			for(double y = -1;y<=1.000001;y+=step)
//				for(double z = -1;z<=1.000001;z+=step)
//					for(double t = -1;t<=1.000001;t+=step)
//						for(double u = -1;u<=1.000001;u+=step)
//						{
//							double vr = FunctionOptimization.f(x, y, z, t, u);
//							if (min > vr)
//							{
//								min = vr;
//								System.out.println(min + " " + x+ " " + y+ " " + z+ " " + t+ " " + u);
//							}
//						}
//		System.out.println("kraj");
		
		
//		Population pop = new Population(Mode.mode.geneSize);
//		new Generations().doNature(pop);
	}
}
